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pmid:38590118

High expression of SULF1 is associated with adverse prognosis in breast cancer brain metastasis.

Yitong Li · Tingting Feng · Qinghong Wang · Yue Wu · Jue Wang · Wenlong Zhang · Qi Kong

Animal models and experimental medicine · 2025 doi:10.1002/ame2.12406

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:38590118
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science-record
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2026-11-01T19:20:33Z
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paper object · 10 fields
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title
High expression of SULF1 is associated with adverse prognosis in breast cancer brain metastasis.
doi
10.1002/ame2.12406
pmid
38590118
authors array · 7 items
[0]
Yitong Li
[1]
Tingting Feng
[2]
Qinghong Wang
[3]
Yue Wu
[4]
Jue Wang
[5]
Wenlong Zhang
[6]
Qi Kong
journal
Animal models and experimental medicine
year
2025
abstract
BACKGROUND: Breast cancer is the most common cancer in women, and in advanced stages, it often metastasizes to the brain. However, research on the biological mechanisms of breast cancer brain metastasis and potential therapeutic targets are limited. METHODS: Differential gene expression analysis (DEGs) for the datasets GSE43837 and GSE125989 from the GEO database was performed using online analysis tools such as GEO2R and Sangerbox. Further investigation related to SULF1 was conducted using online databases such as Kaplan-Meier Plotter and cBioPortal. Thus, expression levels, variations, associations with HER2, biological processes, and pathways involving SULF1 could be analyzed using UALCAN, cBioPortal, GEPIA2, and LinkedOmics databases. Moreover, the sensitivity of SULF1 to existing drugs was explored using drug databases such as RNAactDrug and CADSP. RESULTS: High expression of SULF1 was associated with poor prognosis in advanced breast cancer brain metastasis and was positively correlated with the expression of HER2. In the metastatic breast cancer population, SULF1 ranked top among the 16 DEGs with the highest mutation rate, reaching 11%, primarily due to amplification. KEGG and GSEA analyses revealed that the genes co-expressed with SULF1 were positively enriched in the 'ECM-receptor interaction' gene set and negatively enriched in the 'Ribosome' gene set. Currently, docetaxel and vinorelbine can act as treatment options if the expression of SULF1 is high. CONCLUSIONS: This study, through bioinformatics analysis, unveiled SULF1 as a potential target for treating breast cancer brain metastasis (BM).
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The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) detected the DEGs that were common to both primary BRCA and BM samples. The p value and |log2(fold change)| (|log2FC|) were calculated. Genes that meet the selection criteria, namely, a p value < 0.05 and |log2FC| ≥ 2, were considered DEGs.
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quote
The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) detected the DEGs that were common to both primary BRCA and BM samples. The p value and |log2(fold change)| (|log2FC|) were calculated. Genes that meet the selection criteria, namely, a p value < 0.05 and |log2FC| ≥ 2, were considered DEGs.
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All the data were retrieved and available online, and this research did not involve any experiments on humans or animals.
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In the metastatic breast cancer population, SULF1 ranked top among the 16 DEGs with the highest mutation rate, reaching 11%, primarily due to amplification.
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In the metastatic breast cancer population, SULF1 ranked top among the 16 DEGs with the highest mutation rate, reaching 11%, primarily due to amplification.
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In the metastatic breast cancer population, SULF1 ranked top among the 16 DEGs with the highest mutation rate, reaching 11%, primarily due to amplification.
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In the metastatic breast cancer population, SULF1 ranked top among the 16 DEGs with the highest mutation rate, reaching 11%, primarily due to amplification.
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Prinary breast cancers and brain metastasis
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2026-11-01T15:39:54Z
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GSM1071872
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1352
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A BRCA1 Deficient-Like Signature is Enriched in Breast Cancer Brain Metastases
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The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) detected the DEGs that were common to both primary BRCA and BM samples. The p value and |log2(fold change)| (|log2FC|) were calculated. Genes that meet the selection criteria, namely, a p value < 0.05 and |log2FC| ≥ 2, were considered DEGs.
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However, research on the biological mechanisms of breast cancer brain metastasis and potential therapeutic targets are limited.\nMETHODS: Differential gene expression analysis (DEGs) for the datasets GSE43837 and GSE125989 from the GEO database was performed using online analysis tools such as GEO2R and Sangerbox. Further investigation related to SULF1 was conducted using online databases such as Kaplan-Meier Plotter and cBioPortal. Thus, expression levels, variations, associations with HER2, biological processes, and pathways involving SULF1 could be analyzed using UALCAN, cBioPortal, GEPIA2, and LinkedOmics databases. Moreover, the sensitivity of SULF1 to existing drugs was explored using drug databases such as RNAactDrug and CADSP.\nRESULTS: High expression of SULF1 was associated with poor prognosis in advanced breast cancer brain metastasis and was positively correlated with the expression of HER2. In the metastatic breast cancer population, SULF1 ranked top among the 16 DEGs with the highest mutation rate, reaching 11%, primarily due to amplification. KEGG and GSEA analyses revealed that the genes co-expressed with SULF1 were positively enriched in the 'ECM-receptor interaction' gene set and negatively enriched in the 'Ribosome' gene set. Currently, docetaxel and vinorelbine can act as treatment options if the expression of SULF1 is high.\nCONCLUSIONS: This study, through bioinformatics analysis, unveiled SULF1 as a potential target for treating breast cancer brain metastasis (BM).", "claims": [{"id": "claim-method", "statement": "The GEO2R online analysis tool (https://www.ncbi.nlm.nih.gov/geo/geo2r/) detected the DEGs that were common to both primary BRCA and BM samples. The p value and |log2(fold change)| (|log2FC|) were calculated. 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